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How much VRAM does GLM-5.3 need?

GLM-5.3 needs 425 GB for its weights at 4-bit, 427 GB with an 8K context and 429 GB with 32K.

Parameters
753B
Active per token
40B
Longest context
1M
Released
Aug 2026
License
GLM-5.3 License
Strongest at
Chat, Coding, Agents, Docs

Memory at each precision

Memory GLM-5.3 needs at each precision and context length
PrecisionWeightsWith 8KWith 32KWith 128K
As released (FP8)704 GB705 GB708 GB717 GB
6-bit575 GB577 GB579 GB588 GB
5-bit499 GB501 GB503 GB512 GB
4-bit425 GB427 GB429 GB438 GB
3-bit343 GB345 GB347 GB356 GB
2-bit263 GB265 GB267 GB276 GB
1.6-bit145 GB146 GB149 GB158 GB

One conversation, 16-bit context cache, runtime overhead included.

What runs it

The best way GLM-5.3 runs on common GPUs, Macs and AI boxes
MachineBest fitContextSpeedFirst reply
RTX 3060 12 GBToo big
RTX 4060 Ti 16 GBToo big
RTX 3090Too big
RTX 4090Too big
RTX 5090Too big
2× RTX 3090Too big
RTX PRO 6000 BlackwellToo big
M4 Max 128 GBToo big
M5 Max 128 GBToo big
Ryzen AI Max+ 395 128 GBToo big
DGX Spark 128 GBToo big
M3 Ultra 256 GB1.6-bit384K38 tok/s25 s
M5 Ultra 512 GB3-bit216K28 tok/s7.8 s
H100 SXMToo big
DGX Station GB3001.6-bit960K158 tok/s0.7 s
8× H200 NVLFP81M60 tok/s0.3 s

Best fit is the highest quality, up to 8-bit, that leaves 16K of context. First reply is the wait for a 2K prompt. Speeds are rough, plus or minus 25%.

How to run it

llama.cpp
llama-server -hf unsloth/GLM-5.3-GGUF
vLLM
vllm serve zai-org/GLM-5.3
MLX (Mac)
mlx_lm.chat --model mlx-community/GLM-5.3-4bit

Questions

How much VRAM does GLM-5.3 need?

GLM-5.3 needs 425 GB for its weights at 4-bit, 427 GB with an 8K context and 429 GB with 32K.

Can GLM-5.3 run on an RTX 4090?

Not on one card. The smallest machine here that runs it is the M3 Ultra 256 GB.

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